###########################################################################################
## Retrieve consolidated Global LOTA Data from ProcessTrends.com                         ##
## Plots trends for all 5 LOTA series for latest  month                                  ##                   ##
##                                                                                       ##
## RClimate_trends_5_series_for_latest_month.R                                           ##      
##  Orig Oct 26, 2010                                                                    ##
###########################################################################################
 source("http://processtrends.com/files/RClimate.txt")
 library(ggplot2);library(plotrix)
  mon_name <- c("Janvier", "Février", "Mars", "Avril", "Mai", "Juin", "Juillet", "Août", "Septembre", "Octobre", "Novembre", "Décembre")
 lota <- get_lota()
   mon_n <- as.numeric(substring(lota$yr_mon, 5,6))
   yr_n <- as.numeric(substring(lota$yr_mon, 1,4))
  series <- c("GISS", "Hadley", "NOAA", "RSS", "UAH")
 lota_df <- data.frame(yr_n,mon_n, lota)
 which_mon<- 9
## loop to subset lota for each series for which_mon month
  par(mfcol=c(3,2)); par(mar=c(0.5,1,0,0)); par(oma=c(3.5,3.5,4,1))
  for (s in 1:5) {
    lota_mon <- subset(lota_df, lota_df$mon_n == which_mon)
    plot(lota_mon$yr_frac, lota_mon[,s+4],type="o",ylim=c(-.9, 1), las=1,
    xlab="", las=1,pch=16, cex=0.6, col="black", axes=F)
  abline(h=0, col="grey")
#lissage loess/30 ans polynome degree 1
regloess=loess(lota_mon[,s+4]~ lota_mon$yr_frac, lota_df, span = 30/((max(lota_mon$yr_frac)-min(lota_mon$yr_frac))+1), degree = 1)
u=lota_mon$yr_frac
v=predict(regloess, u)
points(u, v, type = "l", lwd = 2.5, col= "blue")

 c <- nrow(lota_mon)
  last_a <- signif(lota_mon[c,s+4],3)
  last_yr <- lota_mon[c,1]
  last_val_note <- paste(last_yr, " Anom @ ", last_a, sep="")
  points(lota_mon[c,3], lota_mon[c,s+4], type = "p",pch=16, col = "red", cex=0.75)
  text(1885, 0.5, last_val_note, adj=0)
 points(1883, 0.5, type="p", pch=16, cex=0.85, col = "red")
  axis(3, at=NULL, labels=F, tcl=0.5)
  axis(4, at=NULL, labels=F, tcl=0.5)

 ifelse (s != 3 &  s!= 5,
    axis(1, at=NULL, labels=F, tcl=0.5),
    axis(1, at=NULL, labels=T))
   
  ifelse (s <= 3, 
    axis(2, at=NULL, labels=T, las=1, cex=0.75),
    axis(2, at=NULL, tcl=0.5,labels=F))

  box()
  text(1890, 0.7, series[s], adj=0, font=2)
  }
  title<- paste("Anomalies de Températures Globales \n Lissage Loess/30 ans - Mois de ", mon_name[which_mon], sep="")
  mtext(title, 3,1,adj=0.5, cex=1, outer=T, font=2)
  mtext("Température Anomalie - C", 2,2,adj=0.5, outer=T)
  mtext("D Kelly O'Day - http://chartgraphs.wordpress.com + modif ChristianP", 1,2, adj = 0, cex = 0.7, outer=TRUE)
  mtext(format(Sys.time(), "%m/%d/ %Y"), 1, 2, adj = 1, cex = 0.7, outer=TRUE)

###################################################################################################
## loop to calc months ranks by series
  m_anom <- numeric(5)
  m_rank <- numeric(5)
  for (s in 1:5)  {
    s_rank <-rank(lota_mon[,s+4], na.last="keep", ties.method="max")
    s_rank_max <- max(s_rank, na.rm=T)
    s_pos <- (s_rank_max +1)-s_rank
    s_df <- data.frame(lota_mon$yr_n, lota_mon[,s+4],s_pos)
    names(s_df) <- c("yr", "anom", "postion")
    s_df_s <- s_df[order(-s_df$anom),]
    m_anom[s]<-   signif(s_df_s[s_df_s$yr==2010,2],2)
    m_rank[s] <-  s_df_s[s_df_s$yr==2010,3]
  }

#### Make table showing rankings 
 baseline <- c("1951-1980", "1961-1990", "1961-1990", "1979-1998", "1979-1998")
 st_yr <- c(rep(1880,3), rep(1979,2))
 ranking <- data.frame(series,  baseline, m_anom, m_rank)
 names(ranking) <- c("Series", "Moyennes", "Anom °C","Rangs") 

 plot_tab <- function() {
  # par(mar=c(2,2,2,1));par(oma=c(1,1,1,1))
  # par(fin=c(5,4))
   table_title <- paste(mon_name[which_mon],"", last_yr," Récapitulatif", sep="")
   plot(x=c(0,1,2,3), y= c(0,1,2,3), type="n", axes=F,ann=F, xlim=c(0,4), ylim=c(0,4))
   addtable2plot(2,1.5,ranking,bty="o",display.rownames=F,hlines=T,cex=1,
   title=table_title, xjust=0.5, yjust=0.5)
   }
plot_tab()